Temporal Serverless Workers on Cloud Run worker pools
The open-source Temporal execution platform is rapidly becoming a foundational layer of modern software infrastructure — especially for orchestration in distributed systems and AI agent workloads. However, deploying and scaling workers in Temporal comes with unique challenges. Workers poll for tasks instead of serving requests, so request-driven serverless platforms can be an awkward fit. This often results in running worker fleets on Kubernetes or VMs, which you have to manage and pay for continuously. You build a metrics pipeline and tune autoscaling triggers, and scaling still trails bursts because of metrics lag. Every deployment means juggling upgrades and versions, and you pay for that compute whether or not there's work in the queue.
We built Cloud Run worker pools for exactly this kind of pull-based work: Your instances connect to a queue or stream, take the next item, and process it. Starting today, Temporal Cloud, which is the fully...
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